Who Are Your At-Risk Students? Using Data Mining to Target Intervention Efforts

Wednesday, October 16 | 11:30AM–12:20PM | Meeting Room 211A/B
Session Type: Professional Development
Improve targeted intervention by building a model to identify and classify at-risk students using data at your institution—and do it in-house with available data-mining tools. Find out how we did this at New York Institute of Technology and how you can do it as well.

Gain an understanding of the complete life cycle of the At-Risk Student Identification Model. | Learn about the methodology and technologies used to create the model. | Understand how to initiate a similar model.


  • Lalitha Agnihotri

    Senior Learning and Data Scientist, McGraw Hill Education
  • Niyazi Bodur

    CIO, Binghamton University

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